Research Article Open Access

Predicting Battery Charge Depletion in Wireless Sensor Networks Using Received Signal Strength Indicator

Inacio Henrique Yano1, Vitor ChavesDe Oliveira1, Eric Alberto de Mello Fagotto1, Alexandre De Assis Mota1 and Lia Toledo Moreira Mota1
  • 1 Pontifical Catholic University of Campinas, Brazil

Abstract

This article aims to identify an adequate mathematical model to predict battery power depletion at the nodes of a Wireless Sensor Network (WSN), by analyzing the Received Signal Strength Indicator (RSSI). Six general models were tested, the simplest Average model, Linear Regression model, Autoregressive (AR) models and Autoregressive Moving Average (ARMA) models.The selected model (AR) presented a low absolute mean residue and adequately represents the charge depletion process, permitting to predict its behavior and to detect the best moment to replace batteries in the WSN nodes.

Journal of Computer Science
Volume 9 No. 7, 2013, 821-826

DOI: https://doi.org/10.3844/jcssp.2013.821.826

Submitted On: 16 May 2013 Published On: 12 June 2013

How to Cite: Yano, I. H., Oliveira, V. C., Fagotto, E. A. M., Mota, A. D. A. & Mota, L. T. M. (2013). Predicting Battery Charge Depletion in Wireless Sensor Networks Using Received Signal Strength Indicator. Journal of Computer Science, 9(7), 821-826. https://doi.org/10.3844/jcssp.2013.821.826

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Keywords

  • RSSI
  • Battery Discharge
  • System Identification
  • Wireless Sensor Networks
  • Mathematical Model
  • ARMA